Approach
How we run an engagement.
From a business question to a solution that runs — and keeps running after we leave. Every engagement starts with a fixed two-week diagnostic, and senior PMO discipline holds it together throughout.
How we work
From question to delivered solution.
Four stages, from a business question to a solution that runs. The starting point is always the objective or decision that needs to improve — technology comes after that.
- 01
Identify & qualify
We clarify the business question, understand the current situation, and assess whether AI, data, analytics, automation, or process redesign can realistically help.
- A clear view of the business issue, its owner, and the expected result
- A first check of available data, process reality, and feasibility
- A recommendation to proceed, reshape the idea, or stop early
- 02
Scope & prepare
We turn a promising opportunity into a delivery-ready project that both business and technical teams can understand.
- What needs to change in the process and decision flow
- The data, systems, people, and rules required
- A delivery plan with requirements, owners, and acceptance criteria
- 03
Execute & coordinate
We support implementation from the business side and keep technical delivery connected to business outcomes.
- Coordinated work between business, vendors, and technical teams
- Regular checks that the solution still solves the business problem
- Testing, acceptance, stakeholder alignment, and adoption support
- 04
Close, adopt & scale
We help make the solution operational, measurable, and ready for further improvement.
- A working solution embedded into the business process
- Handover, user adoption, and value tracking
- Clear next steps for scaling or improving the solution
What holds it together
PMO is the rigor.
Strong AI capability is the baseline. PMO discipline — scope, sequencing, ownership, shipping under constraint — is what separates a slide-led project from one that runs in production. It is load-bearing, not overhead.
Inside a diagnostic
Two weeks. One sharp picture.
Every engagement we accept starts with a diagnostic. Two weeks, fixed-shape, focused on a single output: a sharp picture of what to ship, what to leave alone, and what proof you need before committing.
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Kick-off and access
Stakeholder map, data access, scope freeze. We name the business question we will answer in two weeks, and the three or four data pulls we need to answer it.
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Investigation
Interviews with the people closest to the operating reality. Hands-on data review. Surfacing the patterns that show up across both — we tell you what we see as we see it, no surprise reveal at the end.
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Synthesis
What to ship, what to leave alone, what proof to commit. A sequenced backlog with effort and impact ranges, and the exit criteria for whichever stage you actually need.
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Readout
A concrete recommendation, presented to the senior team. Decision-ready: enough detail to commit, scoped to avoid over-promising. If the case is not there, we say so.
If the case for an engagement is not there, we say so at the readout. Honest answers beat a sold project.
After the diagnostic
We design for the exit from week one.
If the case is there, we agree on a sequenced engagement: a set of operating outcomes, the milestones that prove them, and the senior counterpart inside your organisation who inherits the system as we ship it. Engagement length is shaped by what is real to ship, not by a default contract length.
When the system is running and the counterpart is operating it, we leave.
Common questions
Straight answers.
- How does KKT actually deliver?
- From a business question to a system that runs after we leave — on a four-step runbook: Identify, Scope, Execute, Close. Strong AI capability is the baseline; PMO discipline — scope, sequencing, ownership, shipping under constraint — is what makes it run in production instead of on slides.
- Are you a fit for a mid-sized retailer?
- Yes — we specialise in fuel retail and mid-sized retail. We start from the business problem you are trying to move: margin, availability, working capital, customer value or productivity, and whether data or AI can shift it.
- What does a two-week diagnostic look like?
- Every engagement we accept starts with a fixed, two-week diagnostic. It has one output: a sharp picture of what to ship, what to leave alone, and what proof you need before committing to a build.
- Why would you turn down work?
- If the diagnostic shows the case isn't there, we say so. We don't take engagements we can't ship into production, and engagement length is shaped by what is real to ship — not by a default contract.
- What is Optimus?
- Our daily operating-intelligence system for fuel-distribution networks: procurement, margin, stockouts and working capital, on connected data. In pilot at Red Petroleum, a 250-station network in Kyrgyzstan.
- What happens after you ship?
- We design for the exit from week one. When the system is running and your senior counterpart is operating it, we leave — it keeps running without us.
Let’s talk about your business problem.
Tell us the problem you are trying to move — margin, cost, availability, customer value, or productivity. We will tell you whether data and AI can realistically help, and what the first step looks like.